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Parisa Torkaman

Parisa Torkaman

Academic rank: Instructor
ORCID:
Education: MSc.
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Faculty: Mathematical Sciences and Statistics
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Research

Title
EVALUATION FOR ESTIMATING OF THE PDF AND THE CDF OF GENERALIZED INVERTED EXPONENTIAL DISTRIBUTION WITH APPLICATION IN INDUSTRY
Type
JournalPaper
Keywords
Generalized inverted exponential, least square, estimator weighted Least Square estimator, percentile estimator
Year
2020
Journal Advances in Mathematics scientific journal
DOI
Researchers Parisa Torkaman

Abstract

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased( UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.